Computerized systems for controlling and/or monitoring manufacturing processes, such as, for example, chemical processes, oil refining, production of pulp and paper, food processing and the like, are well-known in the art. Such systems typically include a network of computer workstations, process controllers and I/O subsystems. The I/O subsystems acquire process information from various sensors and other devices in the processing plant. The workstations organize the process information and present it to a user in a way that permits efficient control and monitoring of the manufacturing process. These systems may perform control functions, monitoring functions, or both. For simplicity, such systems are referred to herein as “process control” systems, despite the fact that they may perform control functions, both control and monitoring functions or only monitoring functions.
Process control systems typically manage both “current” process values (very recent measurements of temperatures, flow rates, pressures, tank levels, desired control set points, valve positions, motor states, etc.) and “historical” process values (measurements or control variable values associated with a specific time in the past). Typically, process data measurements and control variables may be represented by numerical values (e.g., 500 psi, 14.4 gallons per minute). However, some process measurements are more easily understood by process control system operators as words (e.g., OFF, OPEN, PV-HELLO) or strings of words (e.g., “sequence active”, “failed to open”). Process control systems typically include one or more applications that provide displays of numerical historical process values. Typically, these displays include a “numeric value vs. time” graph, often referred to as a “trend chart,” because the multi-segment line connecting the numeric values plotted as a function of time indicates the general direction of the measurement over the period of time represented on the display.
Process control systems also typically manage significant “process event” occurrence information. These process event occurrences record the fact that an event of interest occurred in the control system (e.g., an alarm state was detected, an operator changed the value of a control variable, a hardware fault was detected in the process control system, etc.) at a specific point in time. Process control systems typically include one or more applications that provide a display of process event information. Typically, this kind of information is printed on a logging printer soon after the event is detected. The process event information may be stored and can be displayed by applications that allow viewing of event records in various ways (e.g., ordered by time of occurrence and/or data filtering to display only those records that have certain properties or fields with certain values).
In prior art systems, separate process control applications must be used to display historical process values and process event records. This is a significant disadvantage to users trying to understand the operation of the system through examination of these two types of historical data. Even if the user has developed skills in the use of the individual applications, significant additional skill is typically required to manually coordinate and combine the information from the multiple applications to accurately answer questions about the behavior of the process control system. Typically, combining historical process values and event record information in a single view that can be printed and stored or used in correspondence with other process control personnel has required extensive computer skills with many applications. This has meant that this capability is beyond the ability of many process operators, and only highly trained process engineers can perform these tasks. Thus, the cause/effect relationship to process control is typically beyond the reach of process operators, and opportunities for making improvements in the process control system or in the standard operating procedures for a process plant are overlooked, or are too time-consuming to pursue.